Brain atrophy accelerates cognitive decline in cerebral small vessel disease: the LADIS study

Prevention of Vascular Contributions to Cognitive Impairment and Dementia: The Role of Physical Activity and Exercise

Vascular contributions to cognitive impairment and dementia, specifically cerebral small vessel disease (CSVD), are the second most common cause of dementia. Currently, there are no specific pharmacological treatments for CSVD, and the use of conventional antidementia drugs is not recommended. Exercise has the potential to prevent and mitigate CSVD-related brain damage and improve cognitive function. Mechanistic pathways underlying the neurocognitive benefits of exercise include the control of vascular risk factors, improving endothelial function, and upregulating exerkines. Notably, the therapeutic efficacy of exercise may vary by exercise type (ie, aerobic versus resistance training) and biological sex; thus, studies designed specifically to examine these moderating factors within a CSVD context are needed. Furthermore, future research should prioritize resistance training interventions, given their tremendous therapeutic potential. Addressing these knowledge gaps will help us refine exercise recommendations to maximize their therapeutic impact in the prevention and mitigation of CSVD.

More rapid progression of brain atrophy in patients on peritoneal dialysis compared with hemodialysis: The VCOHP Study

We previously reported that brain atrophy was more severe and progressed more rapidly in patients with end-stage kidney disease on peritoneal dialysis (PD) than those with non-dialysis-dependent chronic kidney disease. However, it remains unknown whether there is a difference between patients on PD and hemodialysis (HD). In total, 73 PD and 34 HD patients who underwent brain magnetic resonance imaging (MRI) were recruited for a cross-sectional analysis. Among them, 42 PD and 25 HD patients who underwent a second brain MRI after 2 years were recruited for a longitudinal analysis. T1-weighted MRI images were analyzed. Total gray matter volume (GMV), total white matter volume, and cerebrospinal fluid volume were segmented, and each volume was quantified using statistical parametric mapping software. The ratio of GMV (GMR) was calculated by dividing GMV by intracranial volume, to adjust for variations in head size. We compared GMR between PD and HD patients in the cross-sectional analysis and the annual change in GMR (AC-GMR) in the longitudinal analysis. In the cross-sectional analysis, age- and sex-adjusted GMR was significantly lower in PD than HD patients [least square mean (LSM): 39.2% vs. 40.0%, P = 0.018]. AC-GMR was significantly greater in PD than HD patients and this difference remained significant even after adjustment for potential confounding factors (LSM: -0.68 vs. -0.28 percentage-points/year, P = 0.011). In conclusion, the present study demonstrated a more rapid progression of brain atrophy in PD patients compared with HD patients. We demonstrated that decline in GMR progressed significantly more rapidly in PD than HD patients independent of potential confounding factors. GMR gray matter volume ratio, HD hemodialysis, PD peritoneal dialysis.

Cortical microstructural involvement in cerebral small vessel disease

Background

In cerebral small vessel disease (CSVD), cortical atrophy occurs at a later stage compared to microstructural abnormalities and therefore cannot be used for monitoring short-term disease progression. We aimed to investigate whether cortical diffusion tensor imaging (DTI) and quantitative (q) magnetic resonance imaging (MRI) are able to detect early microstructural involvement of the cerebral cortex in CSVD.

Materials and Methods

33 CSVD patients without significant cortical or whole-brain atrophy and 16 healthy control subjects were included and underwent structural MRI, DTI and high-resolution qMRI with T2, T2* and T2' mapping at 3 T as well as comprehensive cognitive assessment. After tissue segmentation and reconstruction of the cortical boundaries with the Freesurfer software, DTI and qMRI parameters were saved as surface datasets and averaged across all vertices.

Results

Cortical diffusivity and quantitative T2 values were significantly increased in patients compared to controls (p < 0.05). T2 values correlated significantly positively with white matter hyperintensity (WMH) volume (p < 0.01). Both cortical diffusivity and T2 showed significant negative associations with axonal damage to the white matter fiber tracts (p < 0.05).

Conclusions

Cortical diffusivity and quantitative T2 mapping are suitable to detect microstructural involvement of the cerebral cortex in CSVD and represent promising imaging biomarkers for monitoring disease progression and effects of therapeutical interventions in clinical studies.

Unraveling the link: white matter damage, gray matter atrophy and memory impairment in patients with subcortical ischemic vascular disease

Introduction

Prior MRI studies have shown that patients with subcortical ischemic vascular disease (SIVD) exhibited white matter damage, gray matter atrophy and memory impairment, but the specific characteristics and interrelationships of these abnormal changes have not been fully elucidated.

Materials and methods

We collected the MRI data and memory scores from 29 SIVD patients with cognitive impairment (SIVD-CI), 29 SIVD patients with cognitive unimpaired (SIVD-CU) and 32 normal controls (NC). Subsequently, the thicknesses and volumes of the gray matter regions that are closely related to memory function were automatically assessed using FreeSurfer software. Then, the volume, fractional anisotropy (FA), mean diffusivity (MD), amplitude of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) values of white matter hyperintensity (WMH) region and normal-appearing white matter (NAWM) were obtained using SPM, DPARSF, and FSL software. Finally, the analysis of covariance, spearman correlation and mediation analysis were used to analyze data.

Results

Compared with NC group, patients in SIVD-CI and SIVD-CU groups showed significantly abnormal volume, FA, MD, ALFF, and ReHo values of WMH region and NAWM, as well as significantly decreased volume and thickness values of gray matter regions, mainly including thalamus, middle temporal gyrus and hippocampal subfields such as cornu ammonis (CA) 1. These abnormal changes were significantly correlated with decreased visual, auditory and working memory scores. Compared with the SIVD-CU group, the significant reductions of the left CA2/3, right amygdala, right parasubiculum and NAWM volumes and the significant increases of the MD values in the WMH region and NAWM were found in the SIVD-CI group. And the increased MD values were significantly related to working memory scores. Moreover, the decreased CA1 and thalamus volumes mediated the correlations between the abnormal microstructure indicators in WMH region and the decreased memory scores in the SIVD-CI group.

Conclusion

Patients with SIVD had structural and functional damages in both WMH and NAWM, along with specific gray matter atrophy, which were closely related to memory impairment, especially CA1 atrophy and thalamic atrophy. More importantly, the volumes of some temporomesial regions and the MD values of WMH regions and NAWM may be potentially helpful neuroimaging indicators for distinguishing between SIVD-CI and SIVD-CU patients.

A. SD. A diagnosis model for brain atrophy using deep learning and MRI of type 2 diabetes mellitus

Objective

Type 2 Diabetes Mellitus (T2DM) is linked to cognitive deterioration and anatomical brain abnormalities like cerebral brain atrophy and cerebral diseases. We aim to develop an automatic deep learning-based brain atrophy diagnosis model to detect, segment, classify, and predict the survival rate.

Methods

Two hundred thirty-five MRI images affected with brain atrophy due to prolonged T2DM were acquired. The dataset was divided into training and testing (80:20%; 188, 47, respectively). Pre-processing is done through a novel convolutional median filter, followed by segmentation of atrophy regions, i.e., the brain shrinkage, white and gray matter is done through the proposed TRAU-Net model (Transfer Residual Attention U-Net), classification with the proposed Multinomial Logistic regression with Attention Swin Transformer (MLAST), and prediction of chronological age is determined through Multivariate CoX Regression model (MCR). The classification of Brain Atrophy (BA) types is determined based on the features extracted from the segmented region. Performance measures like confusion matrix, specificity, sensitivity, accuracy, F1-score, and ROC-AUC curve are used to measure classification model performance, whereas, for the segmentation model, pixel accuracy and dice similarity coefficient are applied.

Results

The pixel accuracy and dice coefficient for segmentation were 98.25 and 96.41, respectively. Brain atrophy multi-class classification achieved overall training accuracy is 0.9632 ± 1.325, 0.9677 ± 1.912, 0.9682 ± 1.715, and 0.9521 ± 1.877 for FA, PA, R-MTA, and L-MTA, respectively. The overall AUC-ROC curve for the classification model is 0.9856. The testing and validation accuracy obtained for the proposed model are 0.9379 and 0.9694, respectively. The prediction model's performance is measured using correlation coefficient (r), coefficient determination r2, and Mean Square Error (MSE) and recorded 0.951, 0.904, and 0.5172, respectively.

Conclusion

The brain atrophy diagnosis model consists of sub-models to detect, segment, and classify the atrophy regions using novel deep learning and multivariate mathematical models. The proposed model has outperformed the existing models regarding multi-classification and segmentation; therefore, the automated diagnosis model can be deployed in healthcare centers to assist physicians.

Association of Neuroimaging Markers on Clinical CT Scans With Domain-Specific Cognitive Impairment in the Early and Later Poststroke Stages

BACKGROUND AND OBJECTIVES

Poststroke cognitive impairment (PSCI) is associated with neuroimaging markers, including cortical atrophy and white matter lesions (WMLs), on clinically acquired CT neuroimaging. The objective was to investigate the association between cortical atrophy/WMLs and PSCI in specific cognitive domains in the acute/subacute and chronic stages after stroke, to provide clarity on the relationship between these neuroimaging markers and the temporal evolution of PSCI.

METHODS

We visually assessed cortical atrophy using the Global Cortical Atrophy (GCA) scale and WMLs using the Fazekas scale. Oxford Cognitive Screen or Birmingham Cognitive Screen assessed PSCI at 2 time points (acute/subacute and chronic) in 6 domains (language, memory, number processing, executive function, attention, and praxis). We binarized domain-specific performance as impaired/unimpaired using normative cutoffs. Multivariable linear and logistic regression analyses evaluated associations between GCA/Fazekas scores with acute/subacute and chronic global and domain-specific PSCI, and ANCOVAs examined whether these scores were significantly different in patients with recovered vs persistent PSCI. Age, sex, education, NIHSS, lesion volume, and recurrent stroke were covariates in these analyses.

RESULTS

Among 411 stroke patients (Mdn/IQR age = 76.16/66.84-83.47; 193 female; 346 ischemic stroke; 107 recurrent stroke), GCA and Fazekas scores were not associated with global cognitive impairment in the acute/subacute stage after stroke, but GCA score was associated with chronic global PSCI (B = 0.01, p < 0.001, 95% CI 0.00-0.01). In domain-specific analyses, GCA score was associated with chronic impairment in the memory (B = 0.06, p < 0.001, 95% CI 0.03-0.10) and attention (B = 0.05, p = 0.003, 95% CI 0.02-0.09) domains, and in patients with persistent PSCI, these domains showed significantly higher GCA scores than patients who had recovered (memory: F(1, 157) = 6.63, p = 0.01, η 2 G = 0.04; attention: F(1, 268) = 10.66, p = 0.001, η 2 G = 0.04).

DISCUSSION

This study highlights the potential effect of cortical atrophy on the cognitive recovery process after stroke and demonstrates the prognostic utility of CT neuroimaging for poststroke cognitive outcomes. Clinical neuroimaging could help identify patients at long-term risk of PSCI during acute hospitalization.

Fractal dimension of the cortical gray matter outweighs other brain MRI features as a predictor of transition to dementia in patients with mild cognitive impairment and leukoaraiosis

Background

The relative contribution of changes in the cerebral white matter (WM) and cortical gray matter (GM) to the transition to dementia in patients with mild cognitive impairment (MCI) is not yet established. In this longitudinal study, we aimed to analyze MRI features that may predict the transition to dementia in patients with MCI and T2 hyperintensities in the cerebral WM, also known as leukoaraiosis.

Methods

Sixty-four participants with MCI and moderate to severe leukoaraiosis underwent baseline MRI examinations and annual neuropsychological testing over a 2 year period. The diagnosis of dementia was based on established criteria. We evaluated demographic, neuropsychological, and several MRI features at baseline as predictors of the clinical transition. The MRI features included visually assessed MRI features, such as the number of lacunes, microbleeds, and dilated perivascular spaces, and quantitative MRI features, such as volumes of the cortical GM, hippocampus, T2 hyperintensities, and diffusion indices of the cerebral WM. Additionally, we examined advanced quantitative features such as the fractal dimension (FD) of cortical GM and WM, which represents an index of tissue structural complexity derived from 3D-T1 weighted images. To assess the prediction of transition to dementia, we employed an XGBoost-based machine learning system using SHapley Additive exPlanations (SHAP) values to provide explainability to the machine learning model.

Results

After 2 years, 18 (28.1%) participants had transitioned from MCI to dementia. The area under the receiving operator characteristic curve was 0.69 (0.53, 0.85) [mean (90% confidence interval)]. The cortical GM-FD emerged as the top-ranking predictive feature of transition. Furthermore, aggregated quantitative neuroimaging features outperformed visually assessed MRI features in predicting conversion to dementia.

Discussion

Our findings confirm the complementary roles of cortical GM and WM changes as underlying factors in the development of dementia in subjects with MCI and leukoaraiosis. FD appears to be a biomarker potentially more sensitive than other brain features.

Integrating Neuroimaging Measures in Nursing Research

BACKGROUND

Medical and scientific advancement worldwide has led to a longer lifespan. With the population aging comes the risk of developing cognitive decline. The incorporation of neuroimaging measures in evaluating cognitive changes is limited in nursing research. The aim of this review is to introduce nurse scientists to neuroimaging measures employed to assess the association between brain and cognitive changes.

METHODS

Relevant literature was identified by searching CINAHL, Web of Science, and PubMed databases using the following keywords: "neuroimaging measures," "aging," "cognition," "qualitative scoring," "cognitive ability," "molecular," "structural," and "functional."

RESULTS

Neuroimaging measures can be categorized into structural, functional, and molecular imaging approaches. The structural imaging technique visualizes the anatomical regions of the brain. Visual examination and volumetric segmentation of select structural sequences extract information such as white matter hyperintensities and cerebral atrophy. Functional imaging techniques evaluate brain regions and underlying processes using blood-oxygen-dependent signals. Molecular imaging technique is the real-time visualization of biological processes at the cellular and molecular levels in a given region. Examples of biological measures associated with neurodegeneration include decreased glutamine level, elevated total choline, and elevated Myo-inositol.

DISCUSSION

Nursing is at the forefront of addressing upstream factors impacting health outcomes across a lifespan of a population at increased risk of progressive cognitive decline. Nurse researchers can become more facile in using these measures both in qualitative and quantitative methodology by leveraging previously gathered neuroimaging clinical data for research purposes to better characterize the associations between symptom progression, disease risk, and health outcomes.

Association between morphologic features of intracranial distal arteries and brain atrophy indexes in cerebral small vessel disease: a voxel-based morphometry study

Background

Brain atrophy represents a final common pathway for pathological processes in patients with cerebral small vessel disease (CSVD) and is now recognized as a strong independent predictor of clinical status and progression. The mechanism underlying brain atrophy in patients with CSVD is not yet fully comprehended. This study aims to investigate the association of morphologic features of intracranial distal arteries (A2, M2, P2 and more distal) with different brain structures [gray matter volume (GMV), white matter volume (WMV), and cerebrospinal fluid volume (CSFV)]. Furthermore, we also examined whether a correlation existed between these cerebrovascular characteristics and GMV in different brain regions.

Method

A total of 39 participants were eventually enrolled. The morphologic features of intracranial distal arteries based on TOF-MRA were extracted and quantified using the intracranial artery feature extraction technique (iCafe). The brain 3D-T1 images were segmented into gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF) using the "Segment" tool in CAT12 for the voxel-based morphometry (VBM) analysis. Univariable and multivariable linear regression models were used to investigate the relationship between these cerebrovascular features and different brain structures. Partial correlation analysis with a one-tailed method was used to evaluate the relationship between these cerebrovascular features and GMV in different brain regions.

Results

Our findings indicate that both distal artery length and density were positively correlated with GM fraction in CSVD patients, regardless of whether univariable or multivariable linear regression analyses were performed. In addition, distal artery length (β = -0.428, p = 0.007) and density (β = -0.337, p = 0.036) were also found to be negative associated with CSF fraction, although this relationship disappeared after adjusting for potential confounders. Additional adjustment for the effect of WMHs volume did not change these results. In subgroup anasysis, we found that participants in the highest distal artery length tertile had significantly higher GM fraction and lower CSF fraction level than participants in the lowest distal artery length tertile. In partial correlation analysis, we also found that these cerebrovascular characteristics associated with regional GMV, especially subcortical nuclear.

Conclusion

The morphologic features of intracranial distal arteries, including artery length, density and average tortuosity, measured from 3D-TOF MRA, are associated with generalized or focal atrophy indexes of CSVD.

Central arterial stiffness, brain white matter hyperintensity and total brain volume across the adult lifespan

OBJECTIVES

Mounting evidence suggests that central arterial stiffening is associated with brain ageing in older adults. The purpose of this study was to determine the associations of age with carotid arterial stiffness and carotid-femoral pulse wave velocity (cfPWV), both measurements of central arterial stiffness, the relationship between age-related arterial stiffness, brain white matter hyperintensity (WMH) and total brain volume (TBV), and whether effects of central arterial stiffness on WMH volume and TBV are mediated by pulsatile cerebral blood flow (CBF).

METHODS

One hundred and seventy-eight healthy adults (21-80 years) underwent measurements of central arterial stiffness using tonometry and ultrasonography, WMH and TBV via MRI, and pulsatile CBF at the middle cerebral artery via transcranial Doppler.

RESULTS

Advanced age was associated with increases in both carotid arterial stiffness and cfPWV, increases in WMH volume and decreases in TBV (all P  < 0.01). Multiple linear regression analysis showed that carotid β-stiffness was positively associated with WMH volume (B = 0.015, P  = 0.017) and cfPWV negatively with TBV (B = -0.558, P  < 0.001) after adjustment for age, sex and arterial pressure. Pulsatile CBF mediates the associations between carotid β-stiffness and WMH (95% confidence interval: 0.0001-0.0079).

CONCLUSION

These findings suggest that age-related central arterial stiffness is associated with increased WMH volume and decreased TBV, which is likely mediated by increased arterial pulsation.

White matter and gray matter changes related to cognition in community populations

Objective

Further studies are needed to improve the understanding of the pathological process underlying cognitive impairments. The purpose of this study is to investigate the global and topographic changes of white matter integrity and cortical structure related to cognitive impairments in a community-based population.

Methods

A cross-sectional analysis was performed based on 995 subjects (aged 56.8 ± 9.1 years, 34.8% males) from the Shunyi study, a community-dwelling cohort. Cognitive status was accessed by a series of neurocognitive tests including Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), category Verbal Fluency Test (VFT), Digit Span Test (DST), and Trail Making Tests A and B (TMT-A and TMT-B). Structural and diffusional MRI data were acquired. White matter integrity was assessed using fractional anisotropy (FA), mean diffusivity (MD), and peak width of skeletonized mean diffusivity (PSMD). Cortical surface area, thickness, and volume were measured using Freesurfer. Probabilistic tractography was further conducted to track the white matter fibers connecting to the cortical regions related to cognition. General linear models were used to investigate the association between brain structure and cognition.

Results

Global mean FA and MD were significantly associated with performances in VFT (FA, β 0.119, p &lt; 0.001; MD, β −0.128, p &lt; 0.001). Global cortical surface area, thickness, and volume were not related to cognitive scores. In tract-based spatial statistics analysis, disruptive white matter integrity was related to cognition impairment, mainly in visuomotor processing speed, semantic memory, and executive function (TMT-A and VFT), rather than verbal short-term memory and working memory (DST). In the whole brain vertex-wise analysis, surface area in the left orbitofrontal cortex, right posterior-dorsal part of the cingulate gyrus, and left central sulcus were positively associated with MMSE and MoCA scores, and the association were independent of the connecting white matter tract.

Conclusion

Disrupted white matter integrity and regional cortical surface area were related to cognition in community-dwelling populations. The associations of cortical surface area and cognition were independent of the connecting white matter tract.

Multivariable Analysis of Pre-operative Brain Atrophy as a Predictor of Long Term Mortality After Carotid Endarterectomy

OBJECTIVE

Brain atrophy is associated with an increased mortality rate in elderly trauma patients and in patients treated with mechanical thrombectomy for acute ischaemic stroke. In the setting of ischaemic stroke, the association between brain atrophy and death is stronger than that of sarcopenia. It has previously been shown that lower masseter area, as a marker of sarcopenia, is linked to lower survival after carotid endarterectomy (CEA). The aim of this study was to investigate whether brain atrophy is also associated with long term mortality in patients undergoing CEA.

METHODS

A cohort of patients treated with CEA between 2004 and 2010 was retrieved from the Tampere University Hospital vascular registry and those with available pre-operative computed tomography (CT) imaging were analysed retrospectively. CT images were evaluated for brain atrophy index (BAI) and masseter muscle surface area and density. The association between BAI and mortality was investigated with Cox regression.

RESULTS

Two hundred and thirty-three patients with a median (interquartile range [IQR]) age of 71 years (64.0, 77.0) were included. Most patients were operated on for symptomatic stenosis (n = 203; 87.1%). The median (IQR) duration of follow up was 115.0 months (66.0, 153.0), and 155 patients (66.5%) died during follow up. BAI was statistically significantly correlated with age (r = .489), average masseter density (r = -.202), and smoking (r = -.186; all p <.005). Increased BAI was statistically significantly associated with overall mortality (hazard ratio [HR] 1.45, 95% confidence interval [CI] 1.25 - 1.68, per one standard deviation [SD] increase) in the univariable analysis, and the association remained (HR 1.23, 95% CI 1.04 - 1.46, per one SD increase) in the multivariable models. Age, peripheral artery disease, and chronic obstructive pulmonary disease were also independently associated with mortality. The optimal cutoff value for BAI was 0.133.

CONCLUSION

Brain atrophy independently predicts the long term post-operative mortality rate after CEA in a cohort containing mainly symptomatic patients. Future studies are needed to validate the results in prospective settings and in asymptomatic patients.

Association of Kidney Function Measures With Signs of Neurodegeneration and Small Vessel Disease on Brain Magnetic Resonance Imaging: The Atherosclerosis Risk in Communities (ARIC) Study

RATIONALE & OBJECTIVE

Chronic kidney disease (CKD) is a risk factor for cognitive decline, but evidence is limited on its etiology and morphological manifestation in the brain. We evaluated the association of estimated glomerular filtration rate (eGFR) and urinary albumin-creatinine ratio (UACR) with structural brain abnormalities visible on magnetic resonance imaging (MRI). We also assessed whether this association was altered when different filtration markers were used to estimate GFR.

STUDY DESIGN

Cross-sectional study nested in a cohort study.

SETTING & PARTICIPANTS

1,527 participants in the Atherosclerosis Risk in Communities (ARIC) Study.

PREDICTORS

Log(UACR) and eGFR based on cystatin C, creatinine, cystatin C and creatinine in combination, or β2-microglobulin (B2M).

OUTCOMES

Brain volume reduction, infarcts, microhemorrhages, white matter lesions.

ANALYTICAL APPROACH

Multivariable linear and logistic regression models fit separately for each predictor based on a 1-IQR difference in the predictor value.

RESULTS

Each 1-IQR lower eGFR was associated with reduced cortex volume (regression coefficient: -0.07 [95% CI, -0.12 to-0.02]), greater white matter hyperintensity volume (logarithmically transformed; regression coefficient: 0.07 [95% CI, 0.01-0.15]), and lower white matter fractional anisotropy (regression coefficient: -0.08 [95% CI, -0.17 to-0.01]). The results were similar when eGFR was estimated with different equations based on cystatin C, creatinine, a combination of cystatin C and creatinine, or B2M. Higher log(UACR) was similarly associated with these outcomes as well as brain infarcts and microhemorrhages (odds ratios per 1-IQR-fold greater UACR of 1.31 [95% CI, 1.13-1.52] and 1.30 [95% CI, 1.12-1.51], respectively). The degree to which brain volume was lower in regions usually susceptible to Alzheimer disease and LATE (limbic-predominant age-related TDP-43 [Tar DNA binding protein 43] encephalopathy) was similar to that seen in the rest of the cortex.

LIMITATIONS

No inference about longitudinal effects due to cross-sectional design.

CONCLUSIONS

We found eGFR and UACR are associated with structural brain damage across different domains of etiology, and eGFR- and UACR-related brain atrophy is not selective for regions typically affected by Alzheimer disease and LATE. Hence, Alzheimer disease or LATE may not be leading contributors to neurodegeneration associated with CKD.

Global Cortical Atrophy Is Associated with an Unfavorable Outcome in Stroke Patients on Oral Anticoagulation

INTRODUCTION

Measures of cerebral small vessel disease (cSVD), such as white matter hyperintensities (WMH) and cerebral microbleeds (CMB), are associated with an unfavorable clinical course in stroke patients on oral anticoagulation (OAC) for atrial fibrillation (AF). Here, we investigated whether similar findings can be observed for global cortical atrophy (GCA).

METHODS

Registry-based prospective observational study of 320 patients treated with OAC following AF stroke. Patients underwent magnetic resonance imaging (MRI) allowing assessment of GCA. Using the simplified visual Pasquier scale, the severity of GCA was categorized as follows: 0: no atrophy, 1: mild atrophy; 2: moderate atrophy, and 3: severe atrophy. Using adjusted logistic and Cox regression analysis, we investigated the association of GCA using a composite outcome measure, comprising: (i) recurrent acute ischemic stroke (IS); (ii) intracranial hemorrhage (ICH); and (iii) death.

RESULTS

In our time to event analysis after adjusting for potential confounders (i.e., WMH, CMB, age, sex, diabetes, arterial hypertension, coronary heart disease, hyperlipidemia, and antiplatelet use), GCA was associated with an increased risk for the composite outcome in all three degrees of atrophy (grade 1: aHR 3.95, 95% CI 1.34-11.63, p = 0.013; grade 2: aHR 3.89, 95% CI 1.23-12.30, p = 0.021; grade 3: aHR 4.16, 95% CI 1.17-14.84, p = 0.028).

CONCLUSION

GCA was associated with our composite outcome also after adjusting for other cSVD markers (i.e., CMB, WMH) and age, indicating that GCA may potentially serve as a prognostic marker for stroke patients with atrial fibrillation on oral anticoagulation.

Research on nonstroke dementia screening and cognitive function prediction model for older people based on brain atrophy characteristics

BACKGROUND

Brain atrophy is an important feature in dementia and is meaningful to explore a brain atrophy model to predict dementia. Using machine learning algorithm to establish a dementia model and cognitive function model based on brain atrophy characteristics is unstoppable.

METHOD

We acquired 157 dementia and 156 normal old people.s clinical information and MRI data, which contains 44 brain atrophy features, including visual scale assessment of brain atrophy and multiple linear measurement indexes and brain atrophy index. Five machine learning models were used to establish prediction models for dementia, general cognition, and subcognitive domains.

RESULTS

The extreme Gradient Boosting (XGBoost) model had the best effect in predicting dementia, with a sensitivity of 0.645, a specificity of 0.839, and the area under curve (AUC) of 0.784. In this model, the important brain atrophy features for predicting dementia were temporal horn ratio, cella media index, suprasellar cistern ratio, and the thickness of the corpus callosum genu.

CONCLUSION

For nonstroke elderly people, the machine learning model based on clinical head MRI brain atrophy features had good predictive value for dementia, general cognitive impairment, immediate memory impairment, word fluency disorder, executive dysfunction, and visualspatial disorder.

Genetic polymorphisms in DNA repair genes and their association with risk of cervical cancer: A systematic review and meta-analysis

BACKGROUND

There have been a large number of epidemiologic studies regarding the association between genetic polymorphisms in DNA repair genes and onset of cervical cancer. However, results are inconsistent.

METHODS

Articles published before June 2021 and regarding genetic polymorphisms in DNA repair genes and cervical cancer were searched in following databases: PubMed, Web of Science, Google Scholar, and CNKI. With at least three articles for each polymorphism, we made meta-analysis to compute multivariate odds ratios (ORs) and their 95% confidence intervals (CIs).

RESULTS

The present study showed significant associations between XRCC1 Arg399Gln polymorphisms and risk of cervical cancer in Asian, whereas no significant association between them were showed in Caucasian (Asian: GA vs. GG: OR = 1.27, 95%CI 1.06-1.52; AA vs. GG: OR = 1.91, 95%CI 1.29-2.83; GA + AA vs. GG: OR = 1.36, 95%CI 1.12-1.65; AA vs. GG + GA: OR = 1.66, 95%CI 1.17-2.37; Caucasian: GA vs. GG: OR = 1.08, 95%CI 0.83-1.41; AA vs. GG: OR = 2.18, 95%CI 0.75-6.31; GA + AA vs. GG: OR = 1.23, 95%CI 0.85-1.78; AA vs. GG + GA: OR = 1.70, 95%CI 0.69-4.18). In addition, there were significant associations between ERCC2 rs13181 polymorphisms and risk of cervical cancer in Asian (AC vs AA: OR = 0.53, 95%CI 0.37-0.75, I²  = 0.0%, p value of Q test = 0.847; AC + CC vs AA: OR = 0.50, 95%CI 0.36-0.70, I²  = 0.0%, p value of Q test = 0.856).

CONCLUSIONS

The meta-analysis showed that there were significant associations between XRCC1 Arg399Gln and ERCC2 rs13181 polymorphisms and risk of cervical cancer.

Fully Automatic Classification of Brain Atrophy on NCCT Images in Cerebral Small Vessel Disease: A Pilot Study Using Deep Learning Models

Objective

Brain atrophy is an important imaging characteristic of cerebral small vascular disease (CSVD). Our study explores the linear measurement application on CT images of CSVD patients and develops a fully automatic brain atrophy classification model. The second aim was to compare it with the end-to-end Convolutional Neural Networks (CNNs) model.

Methods

A total of 385 subjects such as 107 no-atrophy brain, 185 mild atrophy, and 93 severe atrophy were collected and randomly separated into training set (n = 308) and test set (n = 77). Key slices for linear measurement were manually identified and used to annotate nine linear measurements and a binary classification of cerebral sulci widening. A linear-measurement-based pipeline (2D model) was constructed for two-types (existence/non-existence brain atrophy) or three-types classification (no/mild atrophy/severe atrophy). For comparison, an end-to-end CNN model (3D-deep learning model) for brain atrophy classification was also developed. Furthermore, age and gender were integrated to the 2D and 3D models. The sensitivity, specificity, accuracy, average F1 score, receiver operating characteristics (ROC) curves for two-type classification and weighed kappa for three-type classification of the two models were compared.

Results

Automated measurement of linear measurements and cerebral sulci widening achieved moderate to almost perfect agreement with manual annotation. In two-type atrophy classification, area under the curves (AUCs) of the 2D model and 3D model were 0.953 and 0.941 with no significant difference (p = 0.250). The Weighted kappa of the 2D model and 3D model were 0.727 and 0.607 according to standard classification they displayed, mild atrophy and severe atrophy, respectively. Applying patient age and gender information improved classification performances of both 2D and 3D models in two-type and three-type classification of brain atrophy.

Conclusion

We provide a model composed of different modules that can classify CSVD-related brain atrophy on CT images automatically, using linear measurement. It has similar performance and better interpretability than the end-to-end CNNs model and may prove advantageous in the clinical setting.

Total Cerebral Small Vessel Disease Burden on MRI Correlates With Medial Temporal Lobe Atrophy and Cognitive Performance in Patients of a Memory Clinic

Background: Cerebral small vessel disease (cSVD) and neurodegeneration are the two main causes of dementia and are considered distinct pathological processes, while studies have shown overlaps and interactions between the two pathological pathways. Medial temporal atrophy (MTA) is considered a classic marker of neurodegeneration. We aimed to investigate the relationship of total cSVD burden and MTA on MRI using a total cSVD score and to explore the impact of the two MRI features on cognition. Methods: Patients in a memory clinic were enrolled, who underwent brain MRI scan and cognitive evaluation within 7 days after the first visit. MTA and total cSVD score were rated using validated visual scales. Cognitive function was assessed by using Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scales. Spearman's correlation and regression models were used to test (i) the association between MTA and total cSVD score as well as each cSVD marker and (ii) the correlation of the MRI features and cognitive status. Results: A total of 312 patients were finally enrolled, with a median age of 75.0 (66.0-80.0) years and 40.7% (127/312) males. All of them finished MRI and MMSE, and 293 subjects finished MoCA. Of note, 71.8% (224/312) of the patients had at least one of the cSVD markers, and 48.7% (152/312) of them had moderate-severe MTA. The total cSVD score was independently associated with MTA levels, after adjusting for age, gender, years of education, and other vascular risk factors (OR 1.191, 95% CI 1.071-1.324, P = 0.001). In regard to individual markers, a significant association existed only between white matter hyperintensities and MTA after adjusting for the factors mentioned above (OR 1.338, 95% CI 1.050-1.704, P = 0.018). Both MTA and total cSVD score were independent risk factors for MMSE ≤ 26 (MTA: OR 1.877, 95% CI 1.407-2.503, P < 0.001; total cSVD score: OR 1.474, 95% CI 1.132-1.921, P = 0.004), and MoCA < 26 (MTA: OR 1.629, 95% CI 1.112-2.388, P = 0.012; total cSVD score: OR 1.520, 95% CI 1.068-2.162, P = 0.020). Among all the cSVD markers, microbleed was found significantly associated with MMSE ≤ 26, while no marker was demonstrated a relationship with MoCA < 26. Conclusion: Cerebral small vessel disease was related to MTA in patients of a memory clinic, and both the MRI features had a significant association with cognitive impairment.

Neurovascular Alterations in Vascular Dementia: Emphasis on Risk Factors

Vascular dementia (VaD) constitutes the second most prevalent cause of dementia in the world after Alzheimer’s disease (AD). VaD regroups heterogeneous neurological conditions in which the decline of cognitive functions, including executive functions, is associated with structural and functional alterations in the cerebral vasculature. Among these cerebrovascular disorders, major stroke, and cerebral small vessel disease (cSVD) constitute the major risk factors for VaD. These conditions alter neurovascular functions leading to blood-brain barrier (BBB) deregulation, neurovascular coupling dysfunction, and inflammation. Accumulation of neurovascular impairments over time underlies the cognitive function decline associated with VaD. Furthermore, several vascular risk factors, such as hypertension, obesity, and diabetes have been shown to exacerbate neurovascular impairments and thus increase VaD prevalence. Importantly, air pollution constitutes an underestimated risk factor that triggers vascular dysfunction via inflammation and oxidative stress. The review summarizes the current knowledge related to the pathological mechanisms linking neurovascular impairments associated with stroke, cSVD, and vascular risk factors with a particular emphasis on air pollution, to VaD etiology and progression. Furthermore, the review discusses the major challenges to fully elucidate the pathobiology of VaD, as well as research directions to outline new therapeutic interventions.

Association of Ischemic Imaging Phenotype With Progression of Brain Atrophy and Cerebrovascular Lesions on MRI: The SMART-MR Study

OBJECTIVE

To investigate the association of silent vascular lesions, imaging negative ischemia, and symptomatic cerebrovascular disease with long-term progression of brain atrophy and cerebrovascular lesions in patients with arterial disease.

METHODS

Within the SMART-MR study, stroke status of participants at baseline was classified as no cerebrovascular disease (reference group, n=829), symptomatic cerebrovascular disease (n=206), silent vascular lesion (n=157), and imaging negative ischemia (n=90) based upon clinical and MRI findings. Using linear mixed models, changes in brain and white matter hyperintensity (WMH) volumes at baseline and during 12 years of follow-up were studied in stroke classifications. Relative risks were estimated for new infarcts during follow-up associated with stroke classifications. Analyses were adjusted for age, sex, cardiovascular risk factors, and medications.

RESULTS

Symptomatic cerebrovascular disease associated with 0.35 SDs (95%CI 0.24-0.47) smaller brain volume and 0.61 SDs (95%CI 0.48-0.74) larger WMH volume at baseline, and increased risk for new infarcts during follow-up (risk ratio (RR) 2.89; 95%CI 2.00-4.16). Silent vascular lesions associated with 0.15 SDs (95%CI 0.01-0.88) smaller brain volume, 0.02 SDs (95%CI 0.01-0.03) steeper brain atrophy slope, and 0.48 SDs (95%CI 0.32-0.64) larger WMH volume at baseline, in addition to increased risk for lacunes (RR 2.08; 95%CI 1.48-2.94). Individuals with imaging negative ischemia had increased risk for cortical infarcts (RR=2.88; 95%CI 2.17-3.82).

CONCLUSIONS

Patients with symptomatic cerebrovascular disease, silent vascular lesions, or imaging negative ischemia have different course of brain volume loss and cerebrovascular lesions development. These findings may have implications for future stroke risk and dementia and need further investigation.

Higher Total Cerebral Small Vessel Disease Burden Was Associated With Mild Cognitive Impairment and Overall Cognitive Dysfunction: A Propensity Score-Matched Case-Control Study

Background and Objective

The combination of neuroimaging and cognition characteristics may provide complementary information for early identification of mild cognitive impairment (MCI). This study aimed to establish the clinical relevance between cerebral small vessel disease (CSVD) burden and MCI and further explored the cognitive characteristics linked to CSVD applying a propensity score matching (PSM) approach.

Methods

The study was designed as a case–control study. All the subjects underwent the standard clinical assessments, neuropsychological testing battery (including global cognition, memory, executive function, and speed and motor control domains), and brain magnetic resonance imaging (MRI). A 1:2 nearest-neighbor matching approach without replacement was employed with a caliper of 0.15 in the PSM approach.

Results

A total of 84 MCI patients and 186 cognitively normal controls were included in this study. After PSM, 74 MCI patients and 129 controls were successfully matched, and the covariate imbalance was well eliminated. Compared with controls, the MCI group had more severe CSVD burden. In the binary logistic regression analysis, CSVD was associated with MCI after adjusting for all confounders. The results of multivariate linear regression analyses showed that higher total MRI CSVD burden was related to the deficit of cognitive performance in global cognition and three important cognitive domains after adjusting for all confounders.

Conclusion

Cerebral small vessel disease was an independent risk factor of MCI. Moreover, higher total MRI CSVD burden was associated with the overall cognitive impairment among middle-aged and elderly Chinese adults.

Cortical Thinning in the Medial Temporal Lobe and Precuneus Is Related to Cognitive Deficits in Patients With Subcortical Ischemic Vascular Disease

Subcortical ischemic vascular disease (SIVD) is a major cause of vascular cognitive impairment (CI) and features extensive atrophy in the cerebral cortex. We aimed to test the hypothesis that cognitive deficits in SIVD are linked to decreased cortical thickness in specific brain regions, which may constitute neuroimaging biomarkers of CI. Sixty-seven SIVD patients without (SIVD-NC, n = 35) and with (SIVD-CI, n = 32) CI and a group of healthy controls (HCs, n = 36) underwent structural magnetic resonance imaging (MRI) and cognitive functional assessments. FreeSurfer was used to preprocess structural MRI data and to calculate and compare cortical thickness. The correlation between cortical thickness and cognitive scores was examined in SIVD patients. Significantly altered cortical thickness in the bilateral insula, middle and inferior temporal lobes, precuneus, and medial temporal lobe (MTL) was identified among the three groups (p < 0.05, Monte Carlo simulation corrected). Post hoc results showed significantly decreased thickness in the bilateral insula and temporal lobe in SIVD-NC and SIVD-CI patients compared with HCs. However, the areas with reduced cortical thickness were larger in SIVD-CI than SIVD-NC patients. SIVD-CI patients had significantly reduced thickness in the bilateral precuneus and left MTL (Bonferroni corrected) compared with SIVD-NC patients when we extracted the mean thickness for each region of interest. In SIVD patients, the thicknesses of the left MTL and bilateral precuneus were positively correlated with immediate recall in the memory test. SIVD might lead to extensive cerebral cortical atrophy, while atrophy in the MTL and precuneus might be associated with memory deficits.

White Matter Fractional Anisotropy Is a Superior Predictor for Cognitive Impairment Than Brain Volumes in Older Adults With Confluent White Matter Hyperintensities

Older patients with confluent white matter hyperintensities (WMHs) on magnetic resonance imaging have an increased risk for the onset of vascular cognitive impairment (VCI). This study investigates the predictive effects of the white matter (WM) fractional anisotropy (FA) and brain volumes on cognitive impairment for those with confluent WMHs. This study enrolled 77 participants with confluent WMHs (Fazekas grade 2 or 3), including 44 with VCI-no dementia (VCIND) and 33 with normal cognition (NC). The mean FA of 20 WM tracts was calculated to evaluate the global WM microstructural integrity, and major WM tracts were reconstructed using probabilistic tractography. Voxel-based morphometry was used to calculate brain volumes for the total gray matter (GM), the hippocampus, and the nucleus basalis of Meynert (NbM). All volumetric assays were corrected for total intracranial volume. All regression analyses were adjusted for age, gender, education, and apolipoprotein E (ApoE) gene ε4 status. Logistic regression analysis revealed that the mean FA value for global WM was the only independent risk factor for VCI (z score of FA: OR = 4.649, 95%CI 1.576-13.712, p = 0.005). The tract-specific FAs were not associated with the risk of cognitive impairment after controlling the mean FA for global WM. The mean FA value was significantly associated with scores of Mini-Mental State Examination (MMSE) and Auditory Verbal Learning Test. A lower FA was also associated with smaller volumes of total GM, hippocampus, and NbM. However, brain volumes were not found to be directly related to cognitive performances, except for an association between the hippocampal volume and MMSE. In conclusion, the mean FA for global WM microstructural integrity is a superior predictor for cognitive impairment than tract-specific FA and brain volumes in people with confluent WMHs.

Cerebral Small Vessel Disease

Cerebral small vessel disease (CSVD) represents a cluster of various vascular disorders with different pathological backgrounds. The advanced vasculature net of cerebral vessels, including small arteries, capillaries, arterioles and venules, is usually affected. Processes of oxidation underlie the pathology of CSVD, promoting the degenerative status of the epithelial layer. There are several classifications of cerebral small vessel diseases; some of them include diseases such as Binswanger’s disease, leukoaraiosis, cerebral microbleeds (CMBs) and lacunar strokes. This paper presents the characteristics of CSVD and the impact of the current knowledge of this topic on the diagnosis and treatment of patients.

Subclinical Cognitive and Neuropsychiatric Correlates and Hippocampal Volume Features of Brain White Matter Hyperintensity in Healthy People

White matter hyperintensities (WMH) are associated with brain aging and behavioral symptoms as a possible consequence of disrupted white matter pathways. In this study, we investigated, in a cohort of asymptomatic subjects aged 50 to 80, the relationship between WMH, hippocampal atrophy, and subtle, preclinical cognitive and neuropsychiatric phenomenology. Thirty healthy subjects with WMH (WMH+) and thirty individuals without (WMH−) underwent comprehensive neuropsychological and neuropsychiatric evaluations and 3 Tesla Magnetic Resonance Imaging scan. The presence, degree of severity, and distribution of WMH were evaluated with a semi-automated algorithm. Volumetric analysis of hippocampal structure was performed through voxel-based morphometry. A multivariable logistic regression analysis indicated that phenomenology of subclinical apathy and anxiety was associated with the presence of WMH. ROI-based analyses showed a volume reduction in the right hippocampus of WMH+. In healthy individuals, WMH are associated with significant preclinical neuropsychiatric phenomenology, as well as hippocampal atrophy, which are considered as risk factors to develop cognitive impairment and dementia.

The role of rehabilitation psychology in stroke care described through case examples

BACKGROUND

A stroke event, sometimes referred to as a cerebrovascular accident (CVA), is a sudden and often traumatic life event that results in life-changing consequences with which affected people must cope. There are nearly 800,000 instances of stroke annually in the U.S. (American Heart Association, 2018). Stroke is the leading cause of disability in adults, and more than one-third of people who survive a stroke will have severe disability in the U.S. (Mayo, 2005). Between 35% and 75% of stroke survivors will have significant cognitive impairment (Tatemichi et al., 1994; Nys et al., 2007). An estimated one-third of people suffer depression after stroke (Hackett et al., 2005), about one-fourth experience significant anxiety (Barker-Collo, 2007), and about one-fifth suffer from insomnia (Leppavuoria et al., 2002). These and other stroke-related psychological issues negatively influence rehabilitation and outcomes through a variety of mechanisms. For example, post-stroke depression has been shown to be related to more negative functional consequences (Kneebone et al., 2000; Matsuzaki et al., 2015). Psychological disturbances may affect rehabilitation outcomes through a reduction in adherence to home exercise programs, reduced energy level, increased fatigue, reduced frustration tolerance, and potentially less motivation and hope about the future.

OBJECTIVES

This manuscript aims to identify and describe the role of rehabilitation psychology in treating these common post-stroke complaints and, ultimately, optimizing post-stroke outcomes via two case examples.

METHODOLOGY

This manuscript describes two cases of individuals in post-acute rehabilitation who had psychological issues which were negatively affecting outcomes.

CONCLUSION

Given the abrupt and significant life-changing nature of stroke, it is often necessary to manage a diverse array of psychological issues that often cannot be simply managed via psychotropic medications. Moreover, an understanding of the patients' emotional adjustment and issues can help them maximize their rehabilitation, recovery, and community integration. For the cases discussed, psychology consultations were central in helping optimize their rehabilitation and functional outcomes.

Microangiopathie cérébrale: du diagnostic à la prise en charge small vessel disease of the brain: Diagnosis and management

Small vessel disease of the brain is commonly identified among ageing people. It causes almost 25% of strokes and is associated with cognitive impairment and dementia as well as gait difficulties. Its diagnosis is usually made on MRI in the presence of deep white matter and basal ganglia hyperintensities as well as deep lacunar infarcts (lacunes), microbleeds and enlarged perivascular spaces. MRI is also of importance to identify the main differential diagnoses including inflammatory disorders, cerebral amyloid angiopathy and other genetic causes of microangiopathy. Small vessel disease is associated with the main vascular risk factors including notably age and hypertension but whether controlling these vascular risk factors is beneficial is still not clear. Here, we provide a comprehensive review underlining the main diagnostic features of cerebral microangiopathy and summarise the main therapeutic approaches (notably blood pressure normalisation and physical activity) used to control its development and prevent strokes as well as the development of cognitive involvement and gait impairment.

Small vessel disease lesion type and brain atrophy: The role of co-occurring amyloid

INTRODUCTION

It is unknown whether different types of small vessel disease (SVD), differentially relate to brain atrophy and if co-occurring Alzheimer's disease pathology affects this relation.

METHODS

In 725 memory clinic patients with SVD (mean age 67 ± 8 years, 48% female) we compared brain volumes of those with moderate/severe white matter hyperintensities (WMHs; n = 326), lacunes (n = 132) and cerebral microbleeds (n = 321) to a reference group with mild WMHs (n = 197), also considering cerebrospinal fluid (CSF) amyloid status in a subset of patients (n = 488).

RESULTS

WMHs and lacunes, but not cerebral microbleeds, were associated with smaller gray matter (GM) volumes. In analyses stratified by CSF amyloid status, WMHs and lacunes were associated with smaller total brain and GM volumes only in amyloid-negative patients. SVD-related atrophy was most evident in frontal (cortical) GM, again predominantly in amyloid-negative patients.

DISCUSSION

Amyloid status modifies the differential relation between SVD lesion type and brain atrophy in memory clinic patients.

Prior placental bed disorders and later dementia: a retrospective Swedish register-based cohort study

OBJECTIVE

To investigate the association between a history of placental bed disorders and later dementia.

DESIGN

Retrospective population-based cohort study.

SETTING

Sweden.

SAMPLE

All women giving birth in Sweden between 1973 and 1993 (1 128 709).

METHODS

Women with and without placental bed disorders (hypertensive disorders of pregnancy including pre-eclampsia, fetal growth restriction, spontaneous preterm labour and birth, preterm premature rupture of membranes, abruptio placenta, late miscarriages) and other pregnancy complications were identified by means of the Swedish Medical Birth Register. International classification of disease was used. Data were linked to other National Registers. Participants were followed up until 2013. The Cox proportional hazards model was used to calculate hazard ratios for women with and without pregnancy complications and were adjusted for possible confounders.

MAIN OUTCOME MEASURES

Diagnosis of vascular dementia and non-vascular dementia.

RESULTS

Adjusted for cardiovascular disease and socio-demographic factors, an increased risk of vascular dementia was shown in women with previous pregnancy-induced hypertension (Hazard ratio [HR] 1.88, 95% CI 1.32-2.69), pre-eclampsia (HR 1.63, 95% CI 1.23-2.16), spontaneous preterm labour and birth (HR 1.65, 95% CI 1.12-2.42) or preterm premature rupture of membranes (HR 1.60, 95% CI 1.08-2.37). No statistically significant increased risk was seen for other pregnancy complications or non-vascular dementia even though many of the point estimates indicated increased risks.

CONCLUSIONS

Women with placental bed disorders have a higher risk for vascular disease. Mechanisms behind the abnormal placentation remain elusive, although maternal constitutional factors, abnormal implantation as well as impaired angiogenesis have been suggested.

TWEETABLE ABSTRACT

Placental bed syndromes associated with vascular dementia even after adjusting for cardiovascular disease.

Imaging of the aging brain and development of MRI signal abnormalities

Major changes occur at the cerebral level with aging. Cerebral atrophy develops progressively. Multiple lesions related to small-vessel diseases are detected in association with cerebral atrophy including white-matter hyperintensities, lacunes, microbleeds, dilated perivascular spaces and cerebral, including cortex, atrophy. The clinical impact and predictive value of these Imaging makers were examined.

Prediction of cognitive performance in old age from spatial probability maps of white matter lesions

The purposes of this study were to explore the association between cognitive performance and white matter lesions (WMLs), and to investigate whether it is possible to predict cognitive impairment using spatial maps of WMLs. These WML maps were produced for 263 elders from the OASIS-3 dataset, and a relevance vector regression (RVR) model was applied to predict neuropsychological performance based on the maps. The association between the spatial distribution of WMLs and cognitive function was examined using diffusion tensor imaging data. WML burden significantly associated with increasing age (r=0.318, p<0.001) and cognitive decline. Eight of 15 neuropsychological measures could be accurately predicted, and the mini-mental state examination (MMSE) test achieved the highest predictive accuracy (CORR=0.28, p<0.003). WMLs located in bilateral tapetum, posterior corona radiata, and thalamic radiation contributed the most prediction power. Diffusion indexes in these regions associated significantly with cognitive performance (axial diffusivity>radial diffusivity>mean diffusivity>fractional anisotropy). These results show that the combination of the extent and location of WMLs exhibit great potential to serve as a generalizable marker of multidomain neurocognitive decline in the aging population. The results may also shed light on the mechanism underlying white matter changes during the progression of cognitive decline and aging.

Global Burden of Small Vessel Disease-Related Brain Changes on MRI Predicts Cognitive and Functional Decline

Supplemental Digital Content is available in the text.

Cerebral small vessel disease is characterized by a wide range of focal and global brain changes. We used a magnetic resonance imaging segmentation tool to quantify multiple types of small vessel disease–related brain changes and examined their individual and combined predictive value on cognitive and functional abilities.

Predicting Dementia in Cerebral Small Vessel Disease Using an Automatic Diffusion Tensor Image Segmentation Technique

Supplemental Digital Content is available in the text.

Cerebral small vessel disease (SVD) is the most common cause of vascular cognitive impairment, with a significant proportion of cases going on to develop dementia. We explore the extent to which diffusion tensor image segmentation technique (DSEG; which characterizes microstructural damage across the cerebrum) predicts both degree of cognitive decline and conversion to dementia, and hence may provide a useful prognostic procedure.

Cerebral small vessel disease: from a focal to a global perspective

Cerebral small vessel disease (SVD) is commonly observed on neuroimaging among elderly individuals and is recognized as a major vascular contributor to dementia, cognitive decline, gait impairment, mood disturbance and stroke. However, clinical symptoms are often highly inconsistent in nature and severity among patients with similar degrees of SVD on brain imaging. Here, we provide a new framework based on new advances in structural and functional neuroimaging that aims to explain the remarkable clinical variation in SVD. First, we discuss the heterogeneous pathology present in SVD lesions despite an identical appearance on imaging and the perilesional and remote effects of these lesions. We review effects of SVD on structural and functional connectivity in the brain, and we discuss how network disruption by SVD can lead to clinical deficits. We address reserve and compensatory mechanisms in SVD and discuss the part played by other age-related pathologies. Finally, we conclude that SVD should be considered a global rather than a focal disease, as the classically recognized focal lesions affect remote brain structures and structural and functional network connections. The large variability in clinical symptoms among patients with SVD can probably be understood by taking into account the heterogeneity of SVD lesions, the effects of SVD beyond the focal lesions, the contribution of neurodegenerative pathologies other than SVD, and the interaction with reserve mechanisms and compensatory mechanisms.

Fractal dimension of cerebral white matter: A consistent feature for prediction of the cognitive performance in patients with small vessel disease and mild cognitive impairment

Patients with cerebral small vessel disease (SVD) frequently show decline in cognitive performance. However, neuroimaging in SVD patients discloses a wide range of brain lesions and alterations so that it is often difficult to understand which of these changes are the most relevant for cognitive decline. It has also become evident that visually-rated alterations do not fully explain the neuroimaging correlates of cognitive decline in SVD. Fractal dimension (FD), a unitless feature of structural complexity that can be computed from high-resolution T₁-weighted images, has been recently applied to the neuroimaging evaluation of the human brain. Indeed, white matter (WM) and cortical gray matter (GM) exhibit an inherent structural complexity that can be measured through the FD.

In our study, we included 64 patients (mean age ± standard deviation, 74.6 ± 6.9, education 7.9 ± 4.2 years, 53% males) with SVD and mild cognitive impairment (MCI), and a control group of 24 healthy subjects (mean age ± standard deviation, 72.3 ± 4.4 years, 50% males). With the aim of assessing whether the FD values of cerebral WM (WM FD) and cortical GM (GM FD) could be valuable structural predictors of cognitive performance in patients with SVD and MCI, we employed a machine learning strategy based on LASSO (least absolute shrinkage and selection operator) regression applied on a set of standard and advanced neuroimaging features in a nested cross-validation (CV) loop. This approach was aimed at 1) choosing the best predictive models, able to reliably predict the individual neuropsychological scores sensitive to attention and executive dysfunctions (prominent features of subcortical vascular cognitive impairment) and 2) identifying a features ranking according to their importance in the model through the assessment of the out-of-sample error.

For each neuropsychological test, using 1000 repetitions of LASSO regression and 5000 random permutations, we found that the statistically significant models were those for the Montreal Cognitive Assessment scores (p-value = .039), Symbol Digit Modalities Test scores (p-value = .039), and Trail Making Test Part A scores (p-value = .025). Significant prediction of these scores was obtained using different sets of neuroimaging features in which the WM FD was the most frequently selected feature.

In conclusion, we showed that a machine learning approach could be useful in SVD research field using standard and advanced neuroimaging features. Our study results raise the possibility that FD may represent a consistent feature in predicting cognitive decline in SVD that can complement standard imaging.

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White matter fractal dimension is altered in small vessel disease patients with MCI.

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White matter complexity's decrease consistently predicts worse cognitive performance.

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Fractal dimension may be a new marker of white matter damage in small vessel disease.

Blood Pressure Control and Protection of the Aging Brain

Hypertension and dementia are both common disorders whose prevalence increases with age. There are multiple mechanisms by which hypertension affects the brain and alters cognition. These include blood flow dynamics, development of large and small vessel pathology and diverse molecular mechanisms including formation of reactive oxygen species and transcriptional cascades. Blood pressure interacts with Alzheimer disease pathology in numerous and unpredictable ways, affecting both β-amyloid and tau deposition, while also interacting with AD genetic risk factors and other metabolic processes. Treatment of hypertension may prevent cognitive decline and dementia, but methodological issues have limited the ability of randomized clinical trials to show this conclusively. Recent studies have raised hope that hypertension treatment may protect the function and structure of the aging brain from advancing to mild cognitive impairment and dementia.

Association of Brain Magnetic Resonance Imaging Signs With Cognitive Outcomes in Persons With Nonimpaired Cognition and Mild Cognitive Impairment

IMPORTANCE

Brain atrophy and vascular lesions contribute to dementia and mild cognitive impairment (MCI) in clinical referral populations. Prospective evidence in older general populations is limited.

OBJECTIVE

To evaluate which magnetic resonance imaging (MRI) signs are independent risk factors for dementia and MCI.

DESIGN, SETTING, AND PARTICIPANTS

This population-based cohort study included 1553 participants sampled from the Atherosclerosis Risk in Communities Study who had brain MRI scans and were dementia free during visit 5 (June 2011 to September 2013). Participants' cognitive status was evaluated through visit 6 (June 2016 to December 2017).

EXPOSURES

Brain regional volumes, microhemorrhages, white matter hyperintensity (WMH) volumes, and infarcts measured on 3-T MRI.

MAIN OUTCOMES AND MEASURES

Cognitive status (dementia, MCI, or nonimpaired cognition) was determined from in-person evaluations. Dementia among participants who missed visit 6 was identified via dementia surveillance and hospital discharge or death certificate codes. Cox proportional hazards models were used to evaluate the risk of dementia in 3 populations: dementia-free participants (N = 1553), participants with nonimpaired cognition (n = 1014), and participants with MCI (n = 539). Complementary log-log models were used for risk of MCI among participants with nonimpaired cognition who also attended visit 6 (n = 767). Models were adjusted for demographic variables, apolipoprotein E ε4 alleles, vascular risk factors, depressive symptoms, and heart failure.

RESULTS

Overall, 212 incident dementia cases were identified among 1553 participants (mean [SD] age at visit 5, 76 [5.2] years; 946 [60.9%] women; 436 [28.1%] African American) with a median (interquartile range) follow-up period of 4.9 (4.3-5.2) years. Significant risk factors of dementia included lower volumes in the Alzheimer disease (AD) signature region, including hippocampus, entorhinal cortex, and surrounding structures (hazard ratio [HR] per 1-SD decrease, 2.40; 95% CI, 1.89-3.04), lobar microhemorrhages (HR, 1.90; 95% CI, 1.30-2.77), higher volumes of WMH (HR per 1-SD increase, 1.44; 95% CI, 1.23-1.69), and lacunar infarcts (HR, 1.66; 95% CI, 1.20-2.31). The AD signature region volume was also consistently associated with both MCI and progression from MCI to dementia, while subcortical microhemorrhages and infarcts contributed less to the progression from MCI to dementia.

CONCLUSIONS AND RELEVANCE

In this study, lower AD signature region volumes, brain microhemorrhages, higher WMH volumes, and infarcts were risk factors associated with dementia in older community-based residents. Vascular changes were more important in the development of MCI than in its progression to dementia, while AD-related signs were important in both stages.

Brain Morphometry and Longitudinal Relaxation Time of Spontaneously Hypertensive Rats (SHRs) in Early and Intermediate Stages of Hypertension Investigated by 3D VFA-SPGR MRI

Cerebral small vessel disease(s) (SVD) results from pathological changes of the small blood vessels in the brain and is common in older people. The diagnostic features by which SVD manifests in brain includes white matter hyperintensities, lacunes, dilated perivascular spaces, microbleeds, and atrophy. In the present study, we use in vivo magnetic resonance imaging (MRI) to characterize brain morphometry and longitudinal relaxation time (T1) of spontaneously hypertensive rats (SHRs) to study the contribution of chronic hypertension to SVD relevant pathology. Male SHR and Wistar-Kyoto (WKY) rats underwent 3D variable flip angle spoiled gradient echo brain MRI at 9.4 T at early (seven weeks old) and established (19 weeks old) stages of hypertension. The derived proton density weighted and T1 images were utilized for morphometry and to characterize T1 properties in gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF). Custom tissue probability maps were constructed for accurate computerized whole brain tissue segmentations and voxel-wise analyses. Characteristic morphological differences between the two strains included enlarged ventricles, smaller corpus callosum (CC) volumes and general 'thinning' of CC in SHR compared to WKY rats at both age groups. While we did not observe parenchymal T1 differences, the T1 of CSF was elevated in SHR compared to controls. Collectively these findings indicate that SHRs develop WM atrophy which is a clinically robust MRI biomarker associated with WM degeneration.

Microvascular blood flow velocities measured with a retinal function imager: inter-eye correlations in healthy controls and an exploration in multiple sclerosis

Background

The retinal microcirculation has been studied in various diseases including multiple sclerosis (MS). However, inter-eye correlations and potential differences of the retinal blood flow velocity (BFV) remain largely unstudied but may be important in guiding eye selection as well as the design and interpretation of studies assessing or utilizing retinal BFV. The primary aim of this study was to determine inter-eye correlations in BFVs in healthy controls (HCs). Since prior studies raise the possibility of reduced BFV in MS eyes, a secondary aim was to compare retinal BFVs between MS eyes, grouped based on optic neuritis (ON) history and HC eyes.

Methods

Macular arteriole and venule BFVs were determined using a retinal function imager (RFI) in both eyes of 20 HCs. One eye from a total of 38 MS patients comprising 13 eyes with ON (MSON) and 25 eyes without ON (MSNON) history were similarly imaged with RFI.

Results

OD (right) and OS (left) BFVs were not significantly different in arterioles (OD: 3.95 ± 0.59 mm/s; OS: 4.08 ± 0.60 mm/s, P = 0.10) or venules (OD: 3.11 ± 0.46 mm/s; OS: 3.23 ± 0.52 mm/s, P = 0.06) in HCs. Very strong inter-eye correlations were also found between arteriolar (r = 0.84, P < 0.001) and venular (r = 0.87, P < 0.001) BFVs in HCs. Arteriolar (3.48 ± 0.88 mm/s) and venular (2.75 ± 0.53 mm/s) BFVs in MSNON eyes were significantly lower than in HC eyes (P = 0.009 and P = 0.005, respectively). Similarly, arteriolar (3.59 ± 0.69 mm/s) and venular (2.80 ± 0.45 mm/s) BFVs in MSON eyes were also significantly lower than in HC eyes (P = 0.046 and P = 0.048, respectively). Arteriolar and venular BFVs in MSON and MSNON eyes did not differ from each other (P = 0.42 and P = 0.48, respectively).

Conclusions

Inter-eye arteriolar and venular BFVs do not differ significantly in HCs and are strongly correlated. Our findings support prior observations that arteriolar and venular BFVs may be reduced in MS eyes. Moreover, this seems to be the case in both MS eyes with and without a history of ON, raising the possibility of global blood flow alterations in MS. Future larger studies are needed to assess differences in BFVs between MSON and MSNON eyes.

Secondary prevention of Alzheimer's dementia: neuroimaging contributions

BACKGROUND

In Alzheimer's disease (AD), pathological changes may arise up to 20 years before the onset of dementia. This pre-dementia window provides a unique opportunity for secondary prevention. However, exposing non-demented subjects to putative therapies requires reliable biomarkers for subject selection, stratification, and monitoring of treatment. Neuroimaging allows the detection of early pathological changes, and longitudinal imaging can assess the effect of interventions on markers of molecular pathology and rates of neurodegeneration. This is of particular importance in pre-dementia AD trials, where clinical outcomes have a limited ability to detect treatment effects within the typical time frame of a clinical trial. We review available evidence for the use of neuroimaging in clinical trials in pre-dementia AD. We appraise currently available imaging markers for subject selection, stratification, outcome measures, and safety in the context of such populations.

MAIN BODY

Amyloid positron emission tomography (PET) is a validated in-vivo marker of fibrillar amyloid plaques. It is appropriate for inclusion in trials targeting the amyloid pathway, as well as to monitor treatment target engagement. Amyloid PET, however, has limited ability to stage the disease and does not perform well as a prognostic marker within the time frame of a pre-dementia AD trial. Structural magnetic resonance imaging (MRI), providing markers of neurodegeneration, can improve the identification of subjects at risk of imminent decline and hence play a role in subject inclusion. Atrophy rates (either hippocampal or whole brain), which can be reliably derived from structural MRI, are useful in tracking disease progression and have the potential to serve as outcome measures. MRI can also be used to assess comorbid vascular pathology and define homogeneous groups for inclusion or for subject stratification. Finally, MRI also plays an important role in trial safety monitoring, particularly the identification of amyloid-related imaging abnormalities (ARIA). Tau PET to measure neurofibrillary tangle burden is currently under development. Evidence to support the use of advanced MRI markers such as resting-state functional MRI, arterial spin labelling, and diffusion tensor imaging in pre-dementia AD is preliminary and requires further validation.

CONCLUSION

We propose a strategy for longitudinal imaging to track early signs of AD including quantitative amyloid PET and yearly multiparametric MRI.

MRI Lesion Load of Cerebral Small Vessel Disease and Cognitive Impairment in Patients With CADASIL

Background and objective: Cerebral autosomal-dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is the best known and the most common monogenic small vessel disease (SVD). Cognitive impairment is an inevitable feature of CADASIL. Total SVD score and global cortical atrophy (GCA) scale were found to be good predictors of poor cognitive performance in community-dwelling adults. We aimed to estimate the association between the total SVD score, GCA scale and the cognitive performance in patients with CADASIL. Methods: We enrolled 20 genetically confirmed CADASIL patients and 20 controls matched by age, gender, and years of education. All participants underwent cognitive assessments to rate the global cognition and individual domain of executive function, information processing speed, memory, language, and visuospatial function. The total SVD score and GCA scale were rated. Results: The CADASIL group performed worse than the controls on all cognition measures. Neither global cognition nor any separate domain of cognition was significantly different among patients grouped by total SVD score. Negative correlations between the GCA score and cognitive performance were observed. Approximately 40% of the variance was explained by the total GCA score in the domains of executive function, information processing speed, and language. The superficial atrophy score was associated with poor performance in most of the domains of cognition. Adding the superficial atrophy score decreased the prediction power of the deep atrophy score on cognitive impairment alone. Conclusions: The GCA score, not the total SVD score, was significantly associated with poor cognitive performance in patients with CADASIL. Adding the superficial atrophy score attenuated the prediction power of the deep atrophy score on cognitive impairment alone.

Cerebral Small Vessel Disease

Cerebral small vessel disease (CSVD) is composed of several diseases affecting the small arteries, arterioles, venules, and capillaries of the brain, and refers to several pathological processes and etiologies. Neuroimaging features of CSVD include recent small subcortical infarcts, lacunes, white matter hyperintensities, perivascular spaces, microbleeds, and brain atrophy. The main clinical manifestations of CSVD include stroke, cognitive decline, dementia, psychiatric disorders, abnormal gait, and urinary incontinence. Currently, there are no specific preventive or therapeutic measures to improve this condition. In this review, we will discuss the pathophysiology, clinical aspects, neuroimaging, progress of research to treat and prevent CSVD and current treatment of this disease.

Increased risk of cognitive impairment and more severe brain lesions in hypertensive compared to non-hypertensive patients with cerebral small vessel disease

Although cerebral small vessel disease (SVD) is traditionally associated with aging and hypertension (HT), there are patients exhibiting sporadic SVD, free of HT. We aimed to investigate the differences in clinical and neuroradiological presentation in SVD patients in reference to the presence of HT as a risk factor (RF). Vascular RF, cognitive and functional status were evaluated in a cohort of 424 patients. Patients were classified in two groups based on the presence of HT. Severity of vascular lesions was assessed using 1.5 T magnetic resonance imaging with Age-Related White Matter Changes scale total score (tARWMC) and Fazekas scale periventricular (PV) and deep subcortical (DS) scores. No difference between groups in age and sex distribution was noted. In univariate analysis, HT was associated with vascular cognitive impairment (vCI) (OR 2.30, 1.53-3.45, P < 0.0001), functional status (OR 1.47, 1.11-1.95, P = 0.007), depression (OR 2.13, 1.23-3.70, P = 0.007), tARWMC (OR 1.10, 1.05-1.16 95% CI, P < 0.0001), Fazekas PV score (OR 1.34, 1.08-1.67 95% CI, P = 0.008), Fazekas DS score (OR 1.95, 1.44-2.63 95% CI, P < 0.0001) and total number of lacunes (OR 1.10, 1.02-1.18 95% CI, P = 0.009). Multivariate logistic regression analysis indicated that HT was an independent RF for vCI (OR 1.74, 1.09-2.76 95% CI, P = 0.020) and higher Fazekas DS score (OR 1.57, 1.11-2.22 95% CI, P = 0.011). The Kaplan-Meier curve of estimates of survival of SVD patients without vCI revealed a higher proportion of patients with HT progressing to vCI over time when compared to HT-free cases. In patients with sporadic SVD, HT is a contributing factor to worse clinical outcomes and neuroradiological presentation.

White Matter Hyperintensities Potentiate Hippocampal Volume Reduction in Non-Demented Older Individuals with Abnormal Amyloid-β

Cerebral small vessel disease (cSVD) and amyloid-β (Aβ) deposition often co-exist in (prodromal) dementia, and both types of pathology have been associated with neurodegeneration. We examined whether cSVD and Aβ have independent or interactive effects on hippocampal volume (HV) in a memory clinic population. We included 87 individuals with clinical diagnoses of Alzheimer's disease (AD) (n = 24), mild cognitive impairment (MCI) (n = 26), and subjective cognitive complaints (SCC) (n = 37). cSVD magnetic resonance imaging markers included white matter hyperintensity (WMH) volume, lacunar infarct presence, and microbleed presence. Aβ pathology was assessed as cerebrospinal fluid-derived Aβ1 - 42 levels and dichotomized into normal or abnormal, and HV was determined by manual volumetric measurements. A linear hierarchical regression approach was applied for the detection of additive or interaction effects between cSVD and Aβ on HV in the total participant group (n = 87) and in the non-demented group (including SCC and MCI individuals only, n = 63). The results revealed that abnormal Aβ and lacunar infarct presence were independently associated with lower HV in the non-demented individuals. Interestingly, Aβ and WMH pathology interacted in the non-demented individuals, such that WMH had a negative effect on HV in individuals with abnormal CSF Aβ42 levels, but not in individuals with normal CSF Aβ42 levels. These associations were not present when individuals with AD were included in the analyses. Our observations suggest that relatively early on in the disease process older individuals with abnormal Aβ levels are at an increased risk of accelerated disease progression when concomitant cSVD is present.